Update app.py

app.py

@@ -259,6 +259,57 @@ def create_and_save_file(content, file_type="md", prompt=None, is_image=False, s
 
     return filename
 
+
+
+ # 🔍Search Glossary 
+# @st.cache_resource
+def search_glossary(query): 
+    all=""
+    st.markdown(f"- {query}")
+    
+    # 🔍Run 1 - ArXiv RAG researcher expert ~-<>-~ Paper Summary & Ask LLM
+    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
+    response2 = client.predict(
+            query,	# str  in 'parameter_13' Textbox component
+            #"mistralai/Mixtral-8x7B-Instruct-v0.1",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
+            #"mistralai/Mistral-7B-Instruct-v0.2",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
+            "google/gemma-7b-it",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
+            True,	# bool  in 'Stream output' Checkbox component
+            api_name="/ask_llm"
+    )
+    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
+    st.markdown(response2)
+
+    # ArXiv searcher ~-<>-~ Paper References - Update with RAG
+    client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
+    response1 = client.predict(
+    		query,	
+    		10,	
+    		"Semantic Search - up to 10 Mar 2024",	# Literal['Semantic Search - up to 10 Mar 2024', 'Arxiv Search - Latest - (EXPERIMENTAL)']  in 'Search Source' Dropdown component
+    		"mistralai/Mixtral-8x7B-Instruct-v0.1",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
+    		api_name="/update_with_rag_md"
+    )
+    st.write('🔍Run of Multi-Agent System Paper References is Complete')
+    responseall = response2 + response1[0] + response1[1]
+    st.markdown(responseall)
+    return responseall
+    
+def display_content_or_image(query):
+    for category, terms in transhuman_glossary.items():
+        for term in terms:
+            if query.lower() in term.lower():
+                st.subheader(f"Found in {category}:")
+                st.write(term)
+                return True  # Return after finding and displaying the first match
+    image_dir = "images"  # Example directory where images are stored
+    image_path = f"{image_dir}/{query}.png"  # Construct image path with query
+    if os.path.exists(image_path):
+        st.image(image_path, caption=f"Image for {query}")
+        return True
+    st.warning("No matching content or image found.")
+    return False
+
+
 # 🎈 Let's modify the main app to be more fun!
 def main():
     st.title("🐙Git🌌Cosmos💫 - Azure Cosmos DB and Github Agent")
@@ -281,16 +332,34 @@ def main():
     if 'cloned_doc' not in st.session_state:
         st.session_state.cloned_doc = None
 
-    # ⚙️ q= Run ArXiv search from query parameters
+    
+    # ⚙️q= Run ArXiv search from query parameters
     try:
         query_params = st.query_params
-        query = (query_params.get('q') or query_params.get('query') or [''])[0]
-        if query:
-            # 🕵️‍♂️ We have a query! Let's process it!
-            process_text(query)
-            st.stop()  # Stop further execution
-    except Exception as e:
+        query = (query_params.get('q') or query_params.get('query') or [''])
+        if len(query) > 1: 
+            #result = search_arxiv(query)
+            result2 = search_glossary(result) 
+    
+            filesearch = PromptPrefix + query
+            st.markdown(filesearch)
+            process_text(filesearch)
+    except:
         st.markdown(' ')
+    
+    if 'action' in st.query_params:
+        action = st.query_params()['action'][0]  # Get the first (or only) 'action' parameter
+        if action == 'show_message':
+            st.success("Showing a message because 'action=show_message' was found in the URL.")
+        elif action == 'clear':
+            clear_query_params()
+            #st.rerun()
+    
+    if 'query' in st.query_params:
+        query = st.query_params['query'][0]  # Get the query parameter
+        # Display content or image based on the query
+        display_content_or_image(query)
+
 
     # 🔐 Automatic Login
     if Key: